Trends in Hail in the United States

Introduction

Hail causes considerable damage to U.S. crops and property, occasionally causes death to farm
animals, but seldom causes loss of human life. The damaging aspects of hailfalls include the
hailstone sizes (average and maximum), number of hailstones per unit area, and associated
winds, and hail risk is a combination of these factors plus the frequency of hail at a point or over
an area. Crop hail losses in recent years nationally are estimated at $1.3 billion annually,
representing between 1 and 2 percent of the annual crop value. Hail losses vary considerably
regionally, representing, for example, 1 to 2 percent of the crop value in the Midwest, 5 to 6
percent of the crops produced in the High Plains, and much less elsewhere in the nation.
Property losses caused be hail have been increasing with time, now appearing to approximate
crop-hail losses in recent years with crudely estimated annual losses of $1 billion.

The long-term trends in hail incidence and hail losses across the United States, and within states
and discrete regions within the nation, were examined using readily available data and results.
Data on hail sufficient to be used in multi-decadal analyses comes from two sources: the records
of hail from the National Weather Service (NWS), and insurance records of hail loss. In
preparing this analysis, I have drawn on the available data bases.

Data. Since the 1890s, the U.S. Weather Bureau (now NWS) has recorded days when
thunder was heard (thunder days) and when hail fell, identified as "hail days." This was done at
the 200+ first-order stations (FOS) across the nation, and these are manned by staff who make
observations around the clock. At the 10,000+ cooperative substations of the NWS manned by
volunteer weather observers, the incidence of hail could be recorded, and considerable
research of these data has shown that weather observers at some stations have, over the years,
accurately recorded the incidence of hail. Data on hail presented in the NWS's Storm
Data, since its publication began in 1955, are unfortunately badly biased and are unsuitable
for temporal analyses of hail or any form of severe local storms. Thus, the hail-day data of the
NWS stations, all FOS and some cooperative stations, are one major data set suitable for
temporal analysis.

The other long-term records of hail are from insurance records of hail-produced loss. These
come from different sources. The crop-hail insurance data have been systematically
collected since 1948 by companies acting through a central association which has compiled the
data and archived it. These data have limitations including the fact that not all farmers have
taken insurance coverage (hail insurance is estimated to cover 25 to 30 percent of all crop losses
caused by hail). Second, records of loss occur only when crops are growing and susceptible to
loss, and this susceptibility to hail damage changes during the growing season and varies
between crops (e.g., tobacco and tea are more susceptible to hail damage than corn). Third,
crop-hail losses for a state or the nation shift with time due to the amount of coverage (liability)
and the crop value, as well as the temporal variations in hail occurrences (which are large).
Fortunately, the industry devised an adjustment factor named "loss cost," which is the amount of
loss per year ($) divided by the annual amount of liability ($) multiplied by $100. The loss cost
values for 1948 to 1996 provide a useful measure of the temporal fluctuations of insured
loss.

The property insurance industry has not kept loss records for hail alone (or for any other
individual form of severe damaging weather). However, since 1949, the industry, through its
centralized Property Claim Services of the American Insurance Services Group, has recorded
each catastrophe, defined as storm situation producing $5 million or more loss to property (not
crops). For each catastrophe, an estimated amount of dollar loss is available along with
the weather factors causing the damage and states where the losses occurred. The catastrophe
data available since 1949 have several biases limiting their use in temporal analyses.
Fortunately, one major insurance company systematically over time made major adjustments to
the catastrophe data base (done each year) to adjust for the ever changing dollar value, for
changes in property density-location, and changing of costs of construction. This "adjusted"
catastrophe data base offers an opportunity to meaningfully examine the temporal trends in
catastrophes related to hail.

Impacts of Hail

Data from the insurance industry were used to assess the trends in the impacts of hail. The
crop-hail loss data began in 1948 and the property catastrophe data base began in 1949. The
following analyses are based on the 1948(9)-1995 period.

Crop-Hail Losses. The national annual values of insured crop-hail losses appear in figure 1, along with amount of liability. This shows ever
increasing losses ranging from $15 million in 1948 to $129 million in 1974, then jumping to
$265 million in 1980, and approaching $400 million in the early 1990s. Liability also climbed
steadily in this 48-year period.

Figure 1 also presents the adjusted loss cost values, seen
as the best way to examine the climatological trends in crop-hail losses. This shows relatively
high values in the 1950s, early 1960s, and again in the early 1990s. After the peak centered at
1962-63, values declined slowly until the recent 3-year high in 1992-1994. The long-term
average loss cost for the U.S. is $2.55, and the highest 3-year loss costs since 1947 are $3.38 in
1961-63, $3.27 in 1954-56, and $3.25 in 1992-94. From a risk standpoint, the recent peak was
preceded by an 11-year period with relatively low-loss cost values, as shown in table 1. This circumstance only acted to emphasize the
recent losses, but when put in a 48-year time frame, the highs in the early 1990s rate third. No
statistically significant long-term trend of decrease or increase in crop-hail losses is evident.
This distribution also illustrates another key aspect of hail loss found at all scales -- the county,
state, region, and national level -- the losses are skewed over time with 1 to 3 years of high losses
often separated by many years (5 to 15) with low losses.

Regionally, one finds startling differences in crop-hail loss trends, a not unexpected outcome
since hail is so notoriously variable in both space and time. As shown in figure 2, upward trends exist in recent years in the Northern
High Plains and since about 1970 in certain East Coast states (VA, NC, SC, and GA).
Conversely, trends in loss costs in the Midwest and Tennessee Valley states show continuing
decreases over the past 30 years.

Property Catastrophes. The adjusted catastrophe data for 1949-1995 were examined to
identify only those events when hail was part of the cause of loss. Hail, as one cause of
damage, was further assessed for those catastrophes when the loss was due only to hail
with wind. Figure 3 presented two curves based on the
pentad values for these "hail-only" catastrophes during 1950-94. One curve shows the frequency
of the hail-only catastrophes, revealing a peak in 1965-69 (30 storms) and a minimum of 5
storms in 1955-59. The frequency distribution does not indicate a long-term trend upwards or
downwards, particularly since 1960. The other curve on figure
3 is based on the average hail-only catastrophe loss values per pentad. This shows peaks
early, in 1950-54 and 1960-64, followed by low values until higher averages re-appeared in
1980-84 and 1990-94. The values of dollar loss per storm for these 177 hail-only catastrophes
suggest a slight downward trend with time.

The top 20 most damaging hail-only catastrophes during 1949-1994 are listed in table 2. This
reveals three important findings. First, the distribution over time is bi-modal with 13 of the 20
events in two pentads, 1960-64 with 7 top storms, and 1990-94 with 6 events. The 1949-54
period had 3 top storms and 1965-69 had 2 events. Thus, the distribution forms an early peak and
a recent one. Second, the storm losses are confined to one or two states with 17 events causing
damage in 1 or 2 states, a much smaller areal extent than found with most weather catastrophes.
Third, the states where the top 20 events most frequently produced property-hail losses formed a
SW-NE oriented area including Texas (8 occurrences), Oklahoma (5), Kansas (4), Missouri (4),
and Illinois (5 occurrences). This distribution likely reflects a combination of large hailstorm
incidence with the target at risk.

Many other weather catastrophes included hail damage along with damages due to two or more
conditions like tornadoes, heavy rains-flooding, high winds, lightning, etc. These cases also
were analyzed and their frequencies per pentad appear in figure
4 is the U.S. population distribution with time. This and other studies of the nation's
weather catastrophe data reveal that the time-related increase in catastrophic events and their
losses is largely a function of the increased target-at-risk, as indicated by population as a
surrogate measure of the property at risk. The insurance company's adjustment is the catastrophe
data for shifting property-at-risk obviously did not capture all the societal changes affecting at
risk, such as to growth of property density by location and the changing value of property.

Furthermore, study of the catastrophe data for events causing >$100 million in losses revealed (figure 5) that the greatest relative increases in catastrophes
have occurred in the southeast and south where population growth has been greatest since 1950.
The annual losses produced by all weather catastrophes causing >$100 million in losses
were divided by U.S. population (figure 6) to obtain a
population normalized time distribution. This reveals an oscillating but generally unchanging
distribution with time. The five peaks are a result of major hurricanes like Hugo and
Andrew.

In summary, the major insurance-based expressions of damaging hailstorms (crops and
property catastrophes for hail-only events) do not suggest long-term trends up or down. They do
show periods lasting from 1 to 5 years with extremely high losses, followed by longer periods of
relatively low loss. upward trends in losses due to hail exist and these are largely a result of the
changing dollar values, questionable construction practices and materials, and growth in the
property at risk.

Hail-Day Data

The hail-day incidence values based on data collected by NWS stations offer an unbiased
evaluation at the time distribution of hail since 1900. Data were available from three states, and
the results for 4 stations (distributed west-east) in Nebraska appear in figure 7. Other than Omaha, these showed low early
(1921-30) values. Then, all stations had high hail values during 1951-1980, followed by low
values for 1981-1990. The values for Texas stations (figure
8) show two trends. Most stations in northwest Texas and the Panhandle show sizable
increases (e.g., San Angelo and Wichita Falls) with time, whereas stations in east and south
Texas showed declines in hail incidence with time (Dallas and Austin). The Illinois stations (figure 9) all display similar time distributions with their
highest values in 1955-79 (when crop-hail loss values were highest), and slowly declining
hail-day frequencies from 1970 to present. Illinois and all other Midwestern states have
experienced continuing declines in crop-hail loss cost values from the mid 1960s to present.

A key finding revealed in the hail-day values for these three states, and in the state values of loss
cost and in the regional shifts of catastrophe frequency, is that trends in hail incidence and
damages vary considerably across the nation, and even within large states like Texas. Since
hail is a product of thunderstorms, available temporal results on thunder-day incidences since
1900, being studied in an on-going project, were examined. The 1901-95 data from 200 FOS
across the U.S., when analyzed statistically to define regions of similar temporal behavior,
defined five discrete regions, each with a different time distribution. Figure 10 presents the results for these five regions that
comprise the 48 contiguous states. Basically, the distribution in the western mountains and the
southeastern U.S. show marked downward trends in thunderstorms since the 1920s. The
incidences of thunderstorms in High Plains and Midwest show an up-then-down distribution
centered on a peak in the 1940s. This is similar to the hail-day distribution in Illinois and
Nebraska. The West Coast stations suggest a slight upward trend with time, whereas the stations
in and adjacent to Texas show a major increase in thunderstorm activity with time, also similar to
the hail-day distributions. These thunder results reflect the findings from the hail data -- different
long-term trends occur in different regions of the nation.

Limitations of the Data

The past text has defined many of the limitations of the existing data on hail to define long-term
trends and measure loss. It is a case of good news/bad news. The crop-hail insurance data bases
offer some useful quantitative measures of loss detrended for shifting practices and dollar values.
However, the crop-hail insurance data base represents only about 25 percent of the actual
crop-hail loss.

The property losses due to hail are not well defined and conflicting information exists. For
example, in 1992 the Property Claims Service declared that "hailstorms across the country (in
1992) ran up a bill of $1.57 billion." yet, their data on all weather catastrophes shows that hail
plus other conditions caused $3.9 billion in insured losses in 1992, and only one storm was a
hail-only event, and it caused losses listed at $275 million. So, where did the $1.57 billion value
come from? Other recent insurance publications have claimed that all losses from catastrophes
listed as caused by 3, 4 or 5 weather conditions were solely due to hail, an amazing
overstatement.

This points to the lack of good data on the property losses due to hail. In an economic
study of hail losses done in 1975, it was shown that crop-hail losses over a 20-year period were
about ten times greater than the property-hail losses. In recent years several major hail-caused
property losses occurred in cities like Denver with $650 million in hail damage in July 1990,
Orlando with $85 million in April 1992, Wichita with $215 million in June 1992, Oklahoma City
with $200 million in April 1992, Dallas with $227 million in April 1995, and $300 million in Ft.
Worth in May 1995. Recall that the insured crop-hail losses during these years were less than
$400 million, and thus, these huge big-city property losses provide annual values in excess of
the crop-hail losses in 1990, 1992, and 1995. This suggests that the ratio of crop to property
losses has drastically shifted, at least in recent years. The results further suggest that property
losses have been increasing with time due largely to the ever increasing property target. The
good news is that the property insurance industry, through its Insurance Institute for Property
Loss Reduction, has begun keeping records of weather-induced property losses.

Unfortunately the NWS hail data since 1900 is only for hail incidence with no other information.
However, careful studies of the cooperative station data have found that some observers also
reported hail sizes when storms occurred. A project will soon start to get the hail-day data for
most of the nation complete for the 1901-196 period. Field studies of hail in Illinois and
Colorado both agree -- most hailstones are windblown, but there is no data to analyze the
temporal aspects of this condition. Inexpensive hail sensors, developed 35 years ago, could be
used at many weather station locations to begin collecting data that would allow measurement of
hailstone sizes, number of hailstones, and the windblown incidence of hail.

Causes of Trends

Several results presented reveal that the growth of population, or property at risk, with increased
urban targets, increased population in storm-prone areas, and higher property values per unit area
have been the major factors behind the ever growing hail losses to both crops and property in the
United States. When these data are normalized to area/density at risk, the time distributions do
not reveal increases since 1950, but rather level 50-year distributions interspersed with
occasional periods of high losses.

A recent study of very costly weather catastrophes, those causing >$100 million per event,
revealed the time trends of these 189 storms (1949-94) were more closely associated with
weather conditions, such as extra-tropical cyclone activity in the U.S. For example, figure 11 illustrates the time distribution of these costly
catastrophes (many due to conditions other than hail) for 1949-94 along with the frequency of
cyclones. A moderately good relationship exists and the constantly increasing population was
not found to be an important factor affecting the fluctuations of these more damaging weather
events. Recall, however, that only 19 of the 177 hail-only catastrophes since 1949 caused losses
>$100,000. The more costly weather catastrophes are a result of hurricanes, massive outbreaks
of tornadoes and associated thunderstorm conditions (including hail), major flooding events, or
severe winter storms.